It may be remarked that earlier investigators have proposed procedures for upgradation of medical image to some extent, such techniques encompassing histogram equalization, adaptive filtering, or filtering approaches using multiple subimage schemata. However, the procedures are generally not adaptable to variable tissue intensities, and hence cannot give optimal enhancement. Moreover, none of the existing image enhancement technique is able to enhance different kinds of image modalities. Recently wavelet-based approach has been used to explore the possibility of selective image improvement, but here there are many more variables involved. In the latter case, the problem is that one has to tune, in advance, to some arbitrary scale-specific or scale-dependent parameters of the wavelets, which may be suboptimal.
The drawbacks and limitations on the existing techniques are that there is usually loss of information as basically a filtering operation is used on the image to filter out energy power residing in the stochastic noise component of the image. These filters lose some content of the image or may cause artifacts, both of which may hamper the diagnosis.
Furthermore, the majority of the above procedures are not tissue-selective nor tissue-adaptive, since, in general, the various structures in the image are enhanced evenly and monotonously together, as mentioned earlier. The existing techniques do not produce variegated contrast level among different regions, however such variegation is much desirable for proper perception of images.
There is actually a topical need of a proper medical image enhancement technique that can operate adaptively on the variegated texture of heterogeneous tissue image. With this desirability in mind, it may be mentioned that the principal of Stochastic Resonance (SR) has been studied by scientists for various applications to physical or biological systems, such as enhancement of sound detection or optical scattering. However, there in no literature available on SR application for medical image enhancement. Of course, the present invention is the first application of SR for diagnostic medical imaging system.
The SR technique of the present invention has proven effective and overcomes certain limitations in the existing techniques as information loss and unwanted artifacts due to filtering. The SR procedure of the present invention administers extra quality to the contrast of an image through the added stochastic fluctuations, and there is minimal power dissipation or information loss in the image.
The SR technique of the present invention is also lesion specific as the image processing operation, namely the stochastic integral transform (SIT), can be adapted locally to enhance the suspicious regions of tissue. The nature of the pixel-adaptive SIT mapping is such that it provides varying contrast in different regions, so that the entire image is neither enhanced equally nor monotonously. Further, the SR technique of the present invention can enhance different kinds of image modalities and has been tested on various lesions and tumours, under different imaging modalities as CT, MRI, etc. and imparts an excellent opportunity to clinicians and radiologists to enhance and diagnose the unclear or latent lesions in an image.
Although some procedures for image upgradation have been proposed, none of the existing techniques promises enhancement without information loss. The SR technique of the present invention enhances the edges of the lesion, delineates the edema segments more clearly, and demarcates the latent structural brain lesions, along with aiding more efficient discrimation of the different zones of the lesion. Furthermore, the SR technique of the present invention is also useful in broad-ranging image processing applications of a general nature.
The SR technique of the present invention enhances medical diagnostic images such as CT and MRI, and also upgrades such images when they are noisy or indistinct. This improvement of the image would help radiologists/clinicians to perform improved diagnosis.
The SR technique of the present invention also provides a general image enhancement technique that can be adapted locally to enhance suspicious regions of tissue.
The SR technique of the present invention also provides varying contrast in different regions, so that the full image is not enhanced equally and monotonously, but there are differential levels of contrast in different regions of the image, thereby leading to increased discriminability.
The SR technique of the present invention also:
counters noise and enhances medical diagnostic images;
delineates edges of a tumour or lesion, the oedema region and the infarction region;
discriminates various structures and zones in the lesion and in the surrounding areas;
is applicable to any imaging modality;
displays increased structuration of the image; and
offers more accurate estimate of the location and degree of the abnormality in the tissue.